FlexNot - Movie Recommendation System with OMDB API

A comprehensive Python Flask web application for movie recommendations using the OMDB (Open Movie Database) API with global movie database and real-time updates.

Features

• Global Movie Database: Access movies from around the world via OMDB API
• Real-time Movie Search: Search and add new movies instantly from OMDB
• Personalized Recommendations: AI-powered content-based filtering using genres and ratings
• User Authentication: Secure login and registration system
• Movie Rating System: Rate movies and get better recommendations
• Advanced Search: Search movies by title, plot, cast, or director
• Watchlist Management: Save movies to watch later
• Responsive Design: Beautiful UI that works on all devices
• Rich Movie Data: Detailed information including awards, box office, runtime, and more

OMDB API Advantages

• Comprehensive Data: Detailed movie information including awards, box office, ratings
• Global Coverage: Movies from all countries and languages
• Real-time Access: Search and add movies instantly
• Rich Metadata: Director, cast, plot, runtime, country, language information
• Free Tier Available: 1000 requests per day for free

Setup Instructions

1. Install Dependencies

pip install -r requirements.txt

2. Get OMDB API Key

1. Visit OMDB API website
2. Choose a plan (free tier available with 1000 requests/day)
3. Register and get your API key
4. Copy your API key

3. Environment Configuration

1. Copy .env.example to .env:

cp .env.example .env

2. Edit .env file and add your OMDB API key:

OMDB_API_KEY=your_actual_omdb_api_key_here
FLASK_SECRET_KEY=your_secret_key_here

4. Run the Application

python app.py

The application will be available at http://localhost:5000

Usage

1. Register: Create a new account to get personalized recommendations
2. Browse Movies: Explore featured movies and new releases
3. Search: Find specific movies using the search functionality
4. Rate Movies: Rate movies you've watched to improve recommendations
5. Add to Watchlist: Save movies to watch later
6. Get Recommendations: Visit your dashboard for personalized suggestions
7. Add New Movies: Search for any movie and it will be added from OMDB

Technology Stack

• Backend: Python Flask
• Database: SQLite with rich movie schema
• Frontend: HTML, CSS (Tailwind), JavaScript
• API: OMDB (Open Movie Database)
• ML: scikit-learn for recommendation algorithms

API Integration Features

This application integrates with OMDB API to provide:

• Real-time Movie Search: Search any movie and add it instantly
• Detailed Movie Information: Plot, cast, director, awards, box office
• Global Movie Coverage: Movies from all countries and languages
• Rich Metadata: Runtime, country, language, awards information
• High-quality Posters: Movie poster images

Recommendation Algorithm

The system uses advanced content-based filtering:

1. Genre Analysis: Analyzes user's preferred movie genres
2. Rating-based Filtering: Considers user's highly-rated movies (4+ stars)
3. Similarity Matching: Finds movies with similar genres and themes
4. Popularity Fallback: Shows popular movies for new users
5. Continuous Learning: Improves recommendations as users rate more movies

Database Schema

• users: User authentication and profile data
• movies: Comprehensive movie information from OMDB
  • IMDB ID, title, plot, poster, release date
  • Ratings, votes, genres, runtime
  • Director, cast, country, language
  • Awards, box office information
• user_ratings: User ratings for movies (1-5 stars)
• watchlist: User's saved movies to watch later

Key Features

Movie Search and Discovery

• Search movies by title, plot, cast, or director
• Instant addition of new movies from OMDB
• Browse by genres, ratings, and release dates

Personalized Experience

• User registration and authentication
• Personal movie ratings and watchlist
• Customized recommendations based on preferences

Rich Movie Information

• Detailed plots and cast information
• Awards and box office data
• High-quality movie posters
• Runtime, country, and language details

API Rate Limits

• Free Tier: 1000 requests per day
• Paid Tiers: Higher limits available
• The app includes intelligent caching to minimize API calls

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is open source and available under the MIT License.

Support

For issues or questions:

1. Check the documentation
2. Review the code comments
3. Create an issue on the repository